Search results for " rando"

Clinic modelling randomised trials (CMRT's) in animals as a new intermediate between biological experiments and randomised clinical trials: applicati…

1998

A GRASP algorithm for constrained two-dimensional non-guillotine cutting problems

2005

This paper presents a greedy randomized adaptive search procedure (GRASP) for the constrained two-dimensional non-guillotine cutting problem, the problem of cutting the rectangular pieces from a large rectangle so as to maximize the value of the pieces cut. We investigate several strategies for the constructive and improvement phases and several choices for critical search parameters. We perform extensive computational experiments with well-known instances previously reported, first to select the best alternatives and then to compare the efficiency of our algorithm with other procedures.

GRASP with path relinking for the orienteering problem

2014

In this paper, we address an optimization problem resulting from the combination of the well-known travelling salesman and knapsack problems. In particular, we target the orienteering problem, originated in the context of sport, which consists of maximizing the total score associated with the vertices visited in a path within the available time. The problem, also known as the selective travelling salesman problem, is NP-hard and can be formulated as an integer linear program. Since the 1980s, several solution methods for this problem have been developed and applied to a variety of fields, particularly in routing and tourism. We propose a heuristic method—based on the Greedy Randomized Adapt…

Statistical analysis of β decays and the effective value of gA in the proton-neutron quasiparticle random-phase approximation framework

2016

We perform a Markov chain Monte Carlo (MCMC) statistical analysis of a number of measured groundstate-to-ground-state single β+/electron-capture and β− decays in the nuclear mass range of A = 62–142. The corresponding experimental comparative half-lives (log f t values) are compared with the theoretical ones obtained by the use of the proton-neutron quasiparticle random-phase approximation (pnQRPA) with G-matrixbased effective interactions. The MCMC analysis is performed separately for 47 isobaric triplets and 28 more extended isobaric chains of nuclei to extract values and uncertainties for the effective axial-vector coupling constant gA in nuclear-structure calculations performed in the p…

ℓ1-Penalized Methods in High-Dimensional Gaussian Markov Random Fields

2016

In the last 20 years, we have witnessed the dramatic development of new data acquisition technologies allowing to collect massive amount of data with relatively low cost. is new feature leads Donoho to define the twenty-first century as the century of data. A major characteristic of this modern data set is that the number of measured variables is larger than the sample size; the word high-dimensional data analysis is referred to the statistical methods developed to make inference with this new kind of data. This chapter is devoted to the study of some of the most recent ℓ1-penalized methods proposed in the literature to make sparse inference in a Gaussian Markov random field (GMRF) defined …

Regularity of Spike Trains and Harmony Perception in a Model of the Auditory System

2011

Spike train regularity of the noisy neural auditory system model under the influence of two sinusoidal signals with different frequencies is investigated. For the increasing ratio m/n of the input signal frequencies (m, n are natural numbers) the linear growth of the regularity is found at the fixed difference (m - n). It is shown that the spike train regularity in the model is high for harmonious chords of input tones and low for dissonant ones.

Fuzzy Distributed Genetic Approaches for Image Segmentation

2010

This paper presents a new image segmentation algorithm (called FDGA-Seg) based on a combination of fuzzy logic, multiagent systems and genetic algorithms. We propose to use a fuzzy representation of the image site labels by introducing some imprecision in the gray tones values. The distributivity of FDGA-Seg comes from the fact that it is designed around a MultiAgent System (MAS) working with two different architectures based on the master-slave and island models. A rich set of experimental segmentation results given by FDGA-Seg is discussed and compared to the ICM results in the last section.

Statistical Shape and Probability Prior Model for Automatic Prostate Segmentation

2011

International audience; Accurate prostate segmentation in Trans Rectal Ultra Sound (TRUS) images is an important step in different clinical applications. However, the development of computer aided automatic prostate segmentation in TRUS images is a challenging task due to low contrast, heterogeneous intensity distribution inside the prostate region, imaging artifacts like shadow, and speckle. Significant variations in prostate shape, size and contrast between the datasets pose further challenges to achieve an accurate segmentation. In this paper we propose to use graph cuts in a Bayesian framework for automatic initialization and propagate multiple mean parametric models derived from princi…

MRF Model-Based Approach for Image Segmentation Using a Chaotic MultiAgent System

2006

In this paper, we propose a new Chaotic MultiAgent System (CMAS) for image segmentation. This CMAS is a distributed system composed of a set of segmentation agents connected to a coordinator agent. Each segmentation agent performs Iterated Conditional Modes (ICM) starting from its own initial image created initially from the observed one by using a chaotic mapping. However, the coordinator agent receives and diversifies these images using a crossover and a chaotic mutation. A chaotic system is successfully used in order to benefit from the special chaotic characteristic features such as ergodic property, stochastic aspect and dependence on initialization. The efficiency of our approach is s…

GRASP & evolutionary path relinking for medical image registration based on point matching

2010

Image registration is a very active research area in computer vision. Image registration methods, aim to find a transformation between two images taken under different conditions. Point matching is an image registration approach based on searching for the right pairing of points between the two images. From this matching, the registration transformation can be inferred by means of numerical methods. In this paper, we tackle the medical image registration problem adapting a new advanced hybrid metaheuristic composed by the GRASP and the evolutionary path relinking algorithms, called G&EvPR. The experiments conducted in this work have shown the good performance of G&EvPR compared to similar a…